Bayerische Motoren Werke had 40 patents in artificial intelligence during Q1 2024. BMW AG filed patents for a road surface classification system using artificial neural networks, a personality-based intelligent personal assistant system, a device for seat occupancy identification using UWB radar and machine learning, a method for additive manufacturing of three-dimensional objects, and a neural network for validating environment maps in vehicles using sensor data. GlobalData’s report on Bayerische Motoren Werke gives a 360-degree view of the company including its patenting strategy. Buy the report here.
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Bayerische Motoren Werke grant share with artificial intelligence as a theme is 30% in Q1 2024. Grant share is based on the ratio of number of grants to total number of patents.
Recent Patents
Application: Method of classifying a road surface object, method of training an artificial neural network, and method of operating a driver warning function or an automated driving function (Patent ID: US20240104940A1)
The patent filed by Bayerische Motoren Werke AG describes a method for classifying road surface objects based on data points representing horizontal and vertical motions of a vehicle driving over the object. These data points are then classified using an artificial neural network to determine the relevance of the road surface object for driver warning or automated driving functions. The method involves providing a set of data points, using image data files to depict scatter plots of the data points, and generating, supplementing, or updating digital maps based on the classification results to assist driver warning or automated driving functions.
Furthermore, the patent details a method for training an artificial neural network to classify road surface objects by providing data points, ground truth data on relevance, clustering data points, and generating image data files for training. The training process involves utilizing a pretrained convolutional neural network, adding a layer for training with scatter plot image data files, and matching the ground truth information to train the network effectively. The patent also includes claims for computing devices configured to execute the classification method, computer programs with instructions for carrying out the method, and computer-readable storage mediums containing instructions for implementing the method.
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GlobalData Patent Analytics tracks bibliographic data, legal events data, point in time patent ownerships, and backward and forward citations from global patenting offices. Textual analysis and official patent classifications are used to group patents into key thematic areas and link them to specific companies across the world’s largest industries.
